TY - GEN
T1 - A multi-objective biogeography-based optimization for virtual machine placement
AU - Zheng, Qinghua
AU - Li, Rui
AU - Li, Xiuqi
AU - Wu, Jie
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/7
Y1 - 2015/7/7
N2 - In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).
AB - In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).
UR - https://www.scopus.com/pages/publications/84941210052
U2 - 10.1109/CCGrid.2015.25
DO - 10.1109/CCGrid.2015.25
M3 - 会议稿件
AN - SCOPUS:84941210052
T3 - Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015
SP - 687
EP - 696
BT - Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015
Y2 - 4 May 2015 through 7 May 2015
ER -